Analyte, e.g., glucose monitoring systems including continuous and discrete monitoring systems generally include a small, lightweight battery powered and microprocessor controlled system which is configured to detect signals proportional to the corresponding measured glucose levels using an electrometer, and RF signals to transmit the collected data. One aspect of certain analyte monitoring systems include a transcutaneous or subcutaneous analyte sensor configuration which is, for example, partially mounted on the skin of a subject whose analyte level is to be monitored. The sensor cell may use a two or three-electrode (work, reference and counter electrodes) configuration driven by a controlled potential (potentiostat) analog circuit connected through a contact system.
The analyte sensor may be configured so that a portion thereof is placed under the skin of the patient so as to detect the analyte levels of the patient, and another segment of the analyte sensor that is in communication with the transmitter unit. The transmitter unit is configured to transmit the analyte levels detected by the sensor over a wireless communication link such as an RF (radio frequency) communication link to a receiver/monitor unit. The receiver/monitor unit performs data analysis, among others on the received analyte levels to generate information pertaining to the monitored analyte levels.
To obtain accurate data from the analyte sensor, calibration using capillary blood glucose measurements is necessary. Typically, blood glucose measurements are obtained using, for example, a blood glucose meter, and the measured blood glucose values are used to calibrate the sensors. Due to a lag factor between the monitored sensor data and the measured blood glucose values, an error, or signal noise such as signal dropouts, is typically introduced in calibration using the monitored data as well as in computing the displayed glucose value. While correcting for the lag factors can minimize the error due to lag in the presence of noise, in the presence of signal dropouts, such error compensation may reduce accuracy of the monitored sensor data.
In view of the foregoing, it would be desirable to have a method and system for providing noise filtering and signal dropout detection and/or compensation in data monitoring systems.